Hidden bad words identification in social Network content
Abstract
With the increase in popularity and availability of different social media platforms, more and more people are finding it easier and easier to communicate with each other all over the world. That is just one of the highlights of social media. Now let us look at the downside of social media. While many people use it for simple communication with friends and family and keeping up with the latest trends and news, others on the other hand are using it for all the wrong reasons including bullying and circulating false information. All of this has led to the development and improvements of things such as the detection of abusive language, hate speech, cyberbullying, and trolling amongst others. Social Media Sites are being tasked to continuously improve their cybersecurity measures to protect their users from cyberbullying.
References
Sood S. O., Antin J., Churchill E. Using crowdsourcing to improve profanity detection // Proc. Of 2012 AAAI Spring Symposium Series. – 2012.
Indurthi V. et al. Identifying and Categorizing Offensive Language in Social Media using Sentence Embeddings // Proc. of SemEval@NAACL-HLT 2019. – 2019.
Pavlopoulos J. et al. Convai at semeval-2019 task 6: Offensive language identification and categorization with perspective and bert // Proceedings of the 13th international Workshop on Semantic Evaluation. – 2019. – P. 571-576.
Thenmozhi D. et al. SSN_NLP at SemEval-2019 Task 6: Offensive Language Identification in Social Media using Traditional and Deep Machine Learning Approaches //Proceedings of the 13th International Workshop on Semantic Evaluation. – 2019. – P. 739-744.
Pathak V. et al. KBCNMUJAL@ HASOC-Dravidian-CodeMix-FIRE2020: Using Machine Learning for Detection of Hate Speech and Offensive Code-Mixed Social Media text //arXiv preprint arXiv:2102.09866. – 2021.
Shastay A. Misidentification of Alphanumeric Symbols in Both Handwritten and ComputerGenerated Information //Home healthcare now. – 2015. – Vol. 33. – №6. – P. 338-339.